May 7, 2009

Electronic Health Records and BI for Doctors

Haven’t been posting here for a while as I’ve been too busy with other more urgent issues. But I’m back, with a new category in which I have quite a lot to say.

I’ve been consulting in Business Intelligence systems for over twenty five years, and it always seemed to me that the health care industry is greatly underserved in this field.  A BI system requires a store of electronically accessible data that can be manipulated to produce measures of performance for both controllable activities and non-controllable results. The value of BI is in demonstrating correlations between the two, from which decisions can be made about how best to allocate enterprise resources to achieve the best business results. By that criterion, health care is a perfect industry in which to apply BI techniques, except for the fact that most health care data is not readily accessible in computer databases.

This year, the American Renewal and Reinvestment Act of 2009 (the stimulus bill) offered incentives to health care enterprises that do business with Medicare for “meaningful use of certified electronic health records”. Depending on the nature of a medical practice, the plan could pay up to $40,000 per practitioner over five years beginning in 2011, enough (it would seem) to offset a significant portion of the investment in an EHR. The estimated time required for a practice, a clinic, or a hospital to convert from paper charts to EHR is about nine to eighteen months, so the stimulus plan aims to get practitioners to start the process now.

So far, it is a losing proposition. Physicians have resisted adopting EHR for years, for several very good reasons.

First and foremost is the cost. It’s a healthy chunk of change, despite the range of available choices (including ASP/SAAS offerings) for the initial investment, and more is likely to be required in the future under normal systems life cycle conditions. And while the incentives in the stimulus plan sound generous, in reality few practitioners will collect anything close to the authorized limits. The plan allows doctors to bill Medicare an additional 15% on each transaction, but Medicare reimbursement rates for routine transactions are so low this premium never adds up to much.

Second, data privacy issues weigh heavily. While it is true that paper charts are awkward to access and work with, they are also for the same reason intrinsically more secure than electronic records. Data security is a significant HIPAA problem that most health practitioners are not very comfortable with.

Third, practitioners are skeptical about the ability to share data electronically with other practitioners and third party payers who use systems different from their own.

Finally, most practitioners are not very comfortable with using a computer in normal clinical operations. They keep notes on paper without thinking, but if they try to do the same thing with a computer they feel that it interferes with patient communication.

I will address the first three of these objections in future posts. The issue of integrating a computer into a medical encounter is a workflow problem that I address with clients in an implementation project. I can say there is no simple solution, and what works for one person might not work for another, even within the same practice. But this is not to say it is intractable. Practitioners should not dwell on it as a reason not to adopt EHR.

Two other hurdles exist that I have not seen addressed in any discussion. One is the problem of displacement, and the other is comparative effectiveness.

“Displacement” is a term for job loss due to technological innovation. EHR automates tasks that currently require two or three full time employees in many medical practices: medical transcription and E&M Coding.

Most doctors have illegible handwriting, largely because of the conditions under which they have to write. They make notes on the patient’s chart in the examining room, and they have other patients waiting. They jot down what they have to as quickly as possible, and that information has to be transcribed so the next person who has to use it can read it. The E&M Coder uses that information to apply the evaluation and maintenance codes to the chart so that the encounter can be billed to the patient and/or the insurer.

EHR substantially reduces the need for both transacription and manual coding. The doctor enters his notes directly onto the electronic patient record either with the keyboard or using handwriting or speech recognition tools in the system. He can later review and update the notes; no other transcription is required. Most systems also automatically apply the E&M codes based on the “discreet data elements” on the chart, and these too can be reviewed and updated by the practitioner based on his notes. So a full time coder is redundant.

If you run a small business, and you know all your employees, and you have to let some go because their functions are no longer necessary, it’s very hard. Frankly, I don’t think most practitioners want to deal with that. It makes EHR a very tough sell, despite its significant benefits.

“Comparative Effectiveness” is compares treatments of specified conditions and their results across many cases. “Pay-for-performance” incentives from insurers and Medicare essentially use comparative effectiveness studies to impose treatment and reimbursement guidelines. EHR provides support for this by making it much easier to collect and aggregate data, and while “pay-for-performance” suggests significant incremental revenue for medical practitioners and institutions, it also means that practitioners can be graded like any other commodity in a competitive market.

The idea of comparison shopping for a doctor the way you do for a car would have been unthinkable when I was growing up. Nowadays, we have all kinds of consumer reporting, such as the annual best doctors report in New York Magazine. But these comparisons are subjective, based more on patients’ relations with their doctors than on any objective measurement. Because EHR can produce objective comparisons, insurers may use them to rank doctors performance. Rankings can be displayed in the insurers’ directories (both on and off line) and can impact the practitioner’s business accordingly.

Frankly, I think that is scaring the hell out of the medical profession, not to mention drug and medical device makers (see the story in the New York Times of May 7, 2009: “New Effort Reopens a Medical Minefield” by Barry Meier ). Comparative effectiveness data can be used by patients, insurers, and governments alike to second-guess the doctors’ decisions, and that is not good for the doctor, the patient, or health care in general.

The thing is, adoption of EHR is going to become mandatory, very likely before 2015. Other third party payers besides Medicare are going to want it to reduce their processing costs. And the kind of decision support information EHR makes possible is going to be critical for health care reform. The cost of health care in this country is out of control, mainly because of the way the health insurance industry does business. Collecting objective information about medical practice and patient progress will ultimately force the insurers to adopt more reasonable positions on reimbursement policy. Health practitioners need to start viewing EHR as a tool for combating bureaucracy, as well as a tool for clinical management.

February 2, 2009

Investing in BI in a Depressed Economy


There can be no doubt in anyone’s mind that the global economy is in a severe recession. We are all feeling it, and it is causing many businesses to put even the most urgent project investments on hold. IT projects are among the first to be slashed because IT is seen as a utility. Improvements in utility services can wait, as long as service levels don’t deteriorate. Business Intelligence systems are always viewed as IT utility services, and companies that don’t already have them don’t view them as a necessity. Yet it is in times like these that BI becomes a critical success factor.

Business Intelligence systems do not, as a rule, deliver new information. Most of the time, they simply deliver established and proven metrics faster and less labor-intensively. BI systems make it easier to access this information, to see how the metrics change over time, and to present them in new contexts using the ad hoc features of the user interface software. But in the absence of such systems, these basic performance metrics can be derived by people using spreadsheets in the course of their principal jobs. It may take a week or more to produce, but if you are doing it you probably just accept that. It is usually not until this derived information becomes highly divergent across multiple reports, and additional time and effort are required to reconcile the data from multiple departments, that managers become interested in BI systems that promise to deliver a “single version of the truth”.

Once a BI system is in place, invariably performance information becomes available to decision makers much sooner than previously. The faster availability of actionable information potentially makes the organization more agile, and therefore more competitive, since decisions can be made sooner, and results of the decisions monitored continuously. This kind of agility in adverse economic conditions can mean the difference between survival and bankruptcy.

All systems projects are of necessity collaborative. The system designer must communicate with the system’s intended users to insure that both have the same understanding of the underlying data and rules the system must incorporate. BI systems must collect and summarize data across many subject areas in the organization, and it is crucial that all users understand the definitions and origins of all the metrics and all the descriptive dimensions. In the development methodology called Joint Application Development (JAD), subject matter experts from all the user constituencies engage in a structured dialog with the system designer and discuss the data and the rules that will be encapsulated in the system. In these JAD sessions, different perceptions about the company mission, Critical Success Factors, Key Performance Indicators, and business processes are discussed and resolved by the participants, and resulting conventions and definitions are incorporated into the system specification.

This same process can and should be applied to reviewing and developing the company’s business plan in an adverse environment. If it is clear that the business needs to change because of environmental pressure, then all the parts of the business entity should be involved in devising a response. Any such response involves changes in resource allocations, which in turn drive changes in business processes. A change in one business process has impact on other business processes, and this impact needs to be understood and anticipated before it become problematic, across the entire enterprise. Subject matter experts from all the affected functional areas need to negotiate how to make the necessary changes. In addition to resource allocations and procedural changes, the review must also identify how the effects of these changes will be monitored and controlled. A BI system is ideally suited to this, so there is compelling logic to incorporating a BI initiative into this kind of enterprise makeover. The process of translating the reorganization plans into a set of data definitions and rules would help to highlight concepts that are not well defined or understood before they become contentious, and would facilitate the total planning process. And the resulting system would come on line in parallel with the new plan, immediately delivering information that reinforces the project goals.

Suppose an extensive business plan revision is not required, but something must be done to cut costs and allocate resources more efficiently. The collaborative JAD approach is again an effective method of pooling the subject matter expertise of the entire enterprise to develop a plan that addresses current and anticipated constraints. It will highlight potentially self-defeating actions (such as layoffs that result in a knowledge drain), and even if it can’t prevent them at least insures that the decision is made with proper due diligence. Once again, piggybacking a BI systems initiative on the process can facilitate the analysis and result in improved monitoring of results and help identify opportunities for improvement.

Finally, in the event that no change to the business model is anticipated, the issue comes down to whether, in the absence of an effective BI system, the enterprise will be in a position to discover and take advantage of new business opportunities, or deal adequately with shifts in the environment. This is a question of organizational agility that in turn depends on communication and goal congruence.

How does your enterprise monitor the performance of business components? Have you established scorecards that all employees can read, and that convey at a glance what they have achieved and how that affects the company’s prospects? If so, is a scorecard available on the next day? The next week? How is it produced? How many man-hours are required to produce it?

If you don’t have such scorecards, how do you communicate the needs of the business to your employees, and with what frequency? How would you assess the level of goal congruence in your organization? How quickly can your business respond to the potential or the actual loss of a major customer? Can it respond at all?

One of the major benefits of a Business Intelligence system is the process that goes into designing it, because it heightens awareness throughout the organization of the enterprise’s mission, its strengths, and its vulnerabilities. The resulting system encapsulates that knowledge in a tool that can be used for management decision making and for employee motivation. That makes a BI system an investment decision you can’t really afford to put off for better times. There may not be any.

November 12, 2008

BLI PostScript

In my previous post, I discussed so-called “Business Leader Intelligence”, or BLI, and described why it could not have, and never will, prevent the kind of debacle we are currently experiencing. Since then, of course, many more words have been spewed by more influential writers than me along the same lines, including Gretchen Morganson’s detailed report on the Merrill Lynch collapse (”How the Thundering Herd Faltered and Fell”, New York Times Sunday Business, November 9, 2008).

One of the more damning, and least surprising, facts reported was that Ahmass L. Fakahany, a “former Exxon executive who oversaw risk management at Merrill, kept the [bond operations unit] machinary humming along by loosening internal controls…removing longstanding employees who ‘walked the floor,’ talking with traders and other workers to figure out what kinds of risks the firm was taking on. … [The] people chosen to replace those employees were loyal to [Stanley J.] O’Neal and his top leutenants. That made them more concerned about achieving their superior’s profit goals … than about monitoring the firm’s risks”.

 Q.E.D.